Kafi-noonoo Text Retrival

This book mainly focuses on the role of stemming in Kafi-noonoo text retrieval area. Stemming may be positive or negative impacts in different language Text Retrieval consequently; it has positive impact in Kafi-noonoo language.We check it with stemming and without stemming using an experiment, as we got Kafi-noonoo text retrieval has better performance than without stemming. For information retrieval experiment purpose, we use 220 Kafi-noonootext files with fifteen sample queries. Data pre-processing steps (tokenization, normalization, stop word removal and stemming) with other tasks like term weighting were preconditions for the vector space model to represent both each document and a given query.

Autorentext

My name is Mareye Zeleke Mekonen , I studied my first degree in Hawassa University in Information Technology program and again I study my Msc in information technology in Jimma University . Now, I am lecturer in Mettu University, Ethiopia. Research area: information retrieval, stemming, sentiment analysis and NLP.